```
library(tidyverse)
## ── Attaching packages ───── tidyverse 1.3.0 ──
## ✓ ggplot2 3.3.0 ✓ purrr 0.3.3
## ✓ tibble 2.1.3 ✓ dplyr 0.8.5
## ✓ tidyr 1.0.2 ✓ stringr 1.4.0
## ✓ readr 1.3.1 ✓ forcats 0.5.0
## ── Conflicts ──────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
Load Files
SNPs<- read.table("23andMe_complete.txt", header = TRUE, sep = "\t")
To adjust figure size {r, fig.width = 6, fig.height = 6}
SNPs$chromosome = ordered(SNPs$chromosome, levels=c(seq(1, 22), "X", "Y", "MT"))
ggplot(data = SNPs) +
geom_bar(mapping = aes(x = genotype, fill = chromosome)) +
coord_polar() +
ggtitle("Total SNPs for each genotype") +
ylab("Total number of SNPs") +
xlab("Genotype")
Plot graph to a pdf outputfile
pdf("SNP_example_plot.pdf", width=6, height=3)
ggplot(data = SNPs) +
geom_bar(mapping = aes(x = chromosome, fill = genotype))
dev.off()
## quartz_off_screen
## 2
Plot graph to a png outputfile
ppi <- 300
png("SNP_example_plot.png", width=6*ppi, height=6*ppi, res=ppi)
ggplot(data = SNPs) +
geom_bar(mapping = aes(x = chromosome, fill = genotype))
dev.off()
## quartz_off_screen
## 2
Genotype counts per chromosome
library(plotly)
##
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
##
## last_plot
## The following object is masked from 'package:stats':
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## filter
## The following object is masked from 'package:graphics':
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## layout
p <- ggplot(data = SNPs) +
geom_bar(mapping = aes(x = genotype, fill = chromosome))
ggplotly(p)
Excercise 1
ggplot(SNPs, aes(x=chromosome)) +
geom_bar(fill = "#6666CC", colour = "black") +
labs(title = "Total SNP Count for Each chromosome")
Exercise 2
mycolors <-c("AA"= "red","AC"= "red", "AG"= "red", "AT"= "red", "CC"= "red", "CG"= "red", "CT"= "red", "DD"= "red", "DI"= "red", "GG"= "red", "GT"= "red", "II"= "red", "TT"= "red", "A" = "orange", "C" = "orange", "G" = "orange", "T" = "orange", "I" = "yellow", "D" = "yellow")
ggplot(SNPs, aes(x=chromosome, fill = genotype)) +
geom_bar() +
scale_fill_manual(values=c("AA"= "red","AC"= "red", "AG"= "red", "AT"= "red", "CC"= "red", "CG"= "red", "CT"= "red", "DD"= "red", "DI"= "red", "GG"= "red", "GT"= "red", "II"= "red", "TT"= "red", "A" = "orange", "C" = "orange", "G" = "orange", "T" = "orange", "I" = "green", "D" = "green", "--" = "green"))
Exercise 3
ppi <- 300
png("exercise3graph.png", width=6*ppi, height=6*ppi, res=ppi)
ggplot(SNPs, aes(x=chromosome, fill = genotype)) +
geom_bar(position = "dodge")
pdf("exercise3graph.pdf", width=6, height=3)
ggplot(SNPs, aes(x=chromosome, fill = genotype)) +
geom_bar(position = "dodge")
dev.off()
## quartz_off_screen
## 2
Individual Genotypes
Exercise 4
ppi <- 2000
png("lab3_ex6.png", width=20*ppi, height=10*ppi, res=ppi)
ggplot(SNPs, aes(x=chromosome, fill = genotype)) +
geom_bar(position = "dodge") +
facet_wrap(~genotype) +
labs(title = "Lab3 ex6") +
theme(axis.title.x = element_text(face="bold", colour="#990000", size=20))